Create a computer vision system using decision tree algorithms to solve a real-world problem : What is computer vision a

The video tutorial introduces the basics of computer vision, explaining how images are represented and features are extracted. It compares human vision to computer vision, highlighting the use of algorithms for image classification. The tutorial discusses the wide range of applications for computer vision, such as in self-driving cars, face recognition, and handwriting recognition. It also addresses the challenges faced in computer vision, including viewpoint variations, camera limitations, lighting conditions, scaling, and object variation. The session concludes with a discussion on the complexity of training algorithms to generalize like humans.

What is the primary goal of computer vision?

How do humans perceive and classify images?

What are some applications of computer vision mentioned in the text?

Why is training a computer to recognize objects challenging?

What are the limitations of cameras in computer vision?

How does lighting affect the performance of computer vision algorithms?

What is object variation and why is it significant in computer vision?